Setting per-field normalisation hyper-parameters for the named-page finding search task

Per-field normalisation has been shown to be effective for Web search tasks, e.g. named-page finding. However, per-field normalisation also suffers from having hyper-parameters to tune on a per-field basis. In this paper, we argue that the purpose of per-field normalisation is to adjust the linear relationship between field length and term frequency. We experiment with standard Web test collections, using three document fields, namely the body of the document, its title, and the anchor text of its incoming links. From our experiments, we find that across different collections, the linear correlation values, given by the optimised hyper-parameter settings, are proportional to the maximum negative linear correlation. Based on this observation, we devise an automatic method for setting the per-field normalisation hyper-parameter values without the use of relevance assessment for tuning. According to the evaluation results, this method is shown to be effective for the body and title fields. In addition, the difficulty in setting the per-field normalisation hyper-parameter for the anchor text field is explained

Ensemble clustering for result diversification

This paper describes the participation of the University of Twente in the Web track of TREC 2012. Our baseline approach uses the Mirex toolkit, an open source tool that sequantially scans all the documents. For result diversification, we experimented with improving the quality of clusters through ensemble clustering. We combined clusters obtained by different clustering methods (such as LDA and K-means) and clusters obtained by using different types of data (such as document text and anchor text). Our two-layer ensemble run performed better than the LDA based diversification and also better than a non-diversification run

Web Page Retrieval by Combining Evidence

The participation of the REINA Research Group in WebCLEF 2005 focused in the monolingual mixed task. Queries or topics are of two types: named and home pages. For both, we first perform a search by thematic contents; for the same query, we do a search in several elements of information from every page (title, some meta tags, anchor text) and then we combine the results. For queries about home pages, we try to detect using a method based in some keywords and their patterns of use. After, a re-rank of the results of the thematic contents retrieval is performed, based on Page-Rank and Centrality coeficients

Coping with noise in a real-world weblog crawler and retrieval system

In this paper we examine the effects of noise when creating a real-world weblog corpus for information retrieval. We focus on the DiffPost (Lee et al. 2008) approach to noise removal from blog pages, examining the difficulties encountered when crawling the blogosphere during the creation of a real-world corpus of blog pages. We introduce and evaluate a number of enhancements to the original DiffPost approach in order to increase the robustness of the algorithm. We then extend DiffPost by looking at the anchor-text to text ratio, and dis- cover that the time-interval between crawls is more impor- tant to the successful application of noise-removal algorithms within the blog context, than any additional improvements to the removal algorithm itself

Lost but not forgotten: finding pages on the unarchived web

Web archives attempt to preserve the fast changing web, yet they will always be incomplete. Due to restrictions in crawling depth, crawling frequency, and restrictive selection policies, large parts of the Web are unarchived and, therefore, lost to posterity. In this paper, we propose an approach to uncover unarchived web pages and websites and to reconstruct different types of descriptions for these pages and sites, based on links and anchor text in the set of crawled pages. We experiment with this approach on the Dutch Web Archive and evaluate the usefulness of page and host-level representations of unarchived content. Our main findings are the following: First, the crawled web contains evidence of a remarkable number of unarchived pages and websites, potentially dramatically increasing the coverage of a Web archive. Second, the link and anchor text have a highly skewed distribution: popular pages such as home pages have more links pointing to them and more terms in the anchor text, but the richness tapers off quickly. Aggregating web page evidence to the host-level leads to significantly richer representations, but the distribution remains skewed. Third, the succinct representation is generally rich enough to uniquely identify pages on the unarchived web: in a known-item search setting we can retrieve unarchived web pages within the first ranks on average, with host-level representations leading to further improvement of the retrieval effectiveness for websites